Processions of trauma in <i>Hiroshima mon amour</i> : Towards an ethics of representation
Bibliographic record
Abstract
ABSTRACTThis article examines Hiroshima mon amour's generative meta-representational sensibilities. I suggest that the film exemplifies an ethics of representation that resists the violence of positivist accounts of history. Resnais and Duras deconstruct the commemorative systems that hold traumatic histories in general, and Hiroshima's singularly traumatic history in particular, in place. The film incites criticism of the injustice that archival discourses enact on the particularities of trauma, and raises questions about the ethics as well as the truth-value of conventional commemorative tropes. I argue that Hiroshima mon amour enacts an Adornian ethic through a representational (self-)deconstruction that complicates, unsettles, but ultimately does not prohibit its own closure. The film demonstrates how the integration of memory, and its incorporation into words and commemorative overtures, facilitates a reductive remembering that is always a kind of forgetting; such integration, I suggest, while to som...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".